You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Is it possible to explain a black box model with Shapley networks?
Suppose, I have a trained CNN model, and I want to get feature attributions for a single image from IMAGENET data set.
The text was updated successfully, but these errors were encountered:
Thanks for your question. ShapNet has been designed to be an intrinsic explanation model, which means that it explains itself and only itself by design.
However, you could learn a ShapNet that mimic the behavior of your model of choice, which could work in theory, but we have no idea how well.
Is it possible to explain a black box model with Shapley networks?
Suppose, I have a trained CNN model, and I want to get feature attributions for a single image from IMAGENET data set.
The text was updated successfully, but these errors were encountered: